4 papers
Tides Need STEMMED: A Locally Operating Spatio-Temporal Mutually Exciting Point Process with Dynamic Network for Improving Opioid Overdose Death Prediction
Che-Yi Liao, Gian-Gabriel P. Garcia, Kamran Paynabar +3
We develop a Spatio-TEMporal Mutually Exciting point process with Dynamic network (STEMMED), i.e., a point process network wherein each node models a unique community-drug event st…
Sinkhorn Distributionally Robust Optimization
Jie Wang, Rui Gao, Yao Xie
We study distributionally robust optimization with Sinkhorn distance -- a variant of Wasserstein distance based on entropic regularization. We derive a convex programming dual refo…
Variable Selection for Kernel Two-Sample Tests
Jie Wang, Santanu S. Dey, Yao Xie
We consider the variable selection problem for two-sample tests, aiming to select the most informative variables to determine whether two collections of samples follow the same dis…
Deep graph kernel point processes
Zheng Dong, Matthew Repasky, Xiuyuan Cheng +1
Point process models are widely used for continuous asynchronous event data, where each data point includes time and additional information called "marks", which can be locations,…